Instructions to use Simonom/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Simonom/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Simonom/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Simonom/results") model = AutoModelForSequenceClassification.from_pretrained("Simonom/results") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1af76bdc0c3aa9cd1067b7b659aa8a19349357e76d13eebe9a642774c3b893b9
- Size of remote file:
- 5.3 kB
- SHA256:
- ce1ab98cd60a6bab127bf238a5d21c4fbcb256a89435ed4d8bb5e80d3bbbf680
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